Quantiphi vs MobiDev: full comparison for 2026
Last updated: July 2026
Quick verdict
Quantiphi (4.4/5) edges ahead of MobiDev (4.2/5) overall. Quantiphi is the better choice for enterprises, especially in financial services, needing AI delivery at scale with strong cloud-native ML platform engineering.. MobiDev is the stronger option for retail, hospitality, and health/fitness companies wanting a mid-size firm with a proven, product-specific AI/ML delivery track record.. The right choice depends on your project size, budget, and required tech stack.
Quantiphi vs MobiDev: head-to-head summary
| Criterion | Quantiphi | MobiDev |
|---|---|---|
| Founded | 2013 | 2009 |
| HQ | Marlborough, Massachusetts, USA | Atlanta, Georgia, USA |
| Team size | 1,001–5,000 | 201–500 |
| Rating | 4.4 / 5 | 4.2 / 5 |
| Best for | Enterprises, especially in financial services, needing AI delivery at scale with strong cloud-native ML platform engineering. | Retail, hospitality, and health/fitness companies wanting a mid-size firm with a proven, product-specific AI/ML delivery track record. |
| Pricing model | Fixed project and managed AI services | Fixed project and dedicated team |
| Min. engagement | Not published | $20K |
| Primary tech stack | Python, TensorFlow, Google Cloud Vertex AI | Python, TensorFlow, OpenCV |
| Industries served | Financial Services, Healthcare, Media, Technology/SaaS | Retail, Hospitality, Health & Fitness, Sports |
Quantiphi vs MobiDev: overview
Quantiphi
Quantiphi is an AI-first digital engineering company founded in 2013 by Vivek Khemani, Asif Hasan, Ritesh Patel, and Reghu Hariharan, headquartered in Marlborough, Massachusetts. Reported headcount is roughly 2,670–3,927 employees depending on source, making it one of the larger, more established AI-native firms on this list, with strong focus on financial services and cloud-native ML platform engineering.
MobiDev
MobiDev is a custom software development company founded in 2009, headquartered in Atlanta, Georgia, with R&D centers in Lodz, Poland and Chernivtsi, Ukraine, and roughly 290–400 engineers. CEO Oleg Lola initiated a dedicated AI/ML practice in 2018, and the company has since delivered more than 65 AI/ML products, concentrated in retail, hospitality, fitness, sports, and health/wellness.
Services and capabilities: Quantiphi vs MobiDev
| Capability | Quantiphi | MobiDev |
|---|---|---|
| Custom ML model development | ✓ | ✓ |
| Deep learning & computer vision | ✗ | ✓ |
| NLP & LLM / Generative AI | ✗ | ✗ |
| MLOps & production deployment | ✓ | ✗ |
| Data engineering | ✓ | ✓ |
| AI strategy consulting | ✓ | ✗ |
| Staff augmentation | ✗ | ✓ |
Tech stack comparison: Quantiphi vs MobiDev
| Framework / platform | Quantiphi | MobiDev |
|---|---|---|
| Python | ✓ | ✓ |
| TensorFlow | ✓ | ✓ |
| PyTorch | N/A | N/A |
| AWS | ✓ | ✓ |
| Azure | N/A | N/A |
| Google Cloud | ✓ | N/A |
| Kubernetes | ✓ | N/A |
| Databricks | N/A | N/A |
| LangChain | N/A | N/A |
Pricing comparison: Quantiphi vs MobiDev
| Criterion | Quantiphi | MobiDev |
|---|---|---|
| Minimum engagement | Not published | $20K |
| Engagement models | Fixed project, Managed services | Fixed project, Dedicated team |
| Rate transparency | Not public | Minimum disclosed |
| Price tier | Enterprise / not published | Accessible |
Target audience comparison: Quantiphi vs MobiDev
| Dimension | Quantiphi | MobiDev |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Financial Services, Healthcare, Media | Retail, Hospitality, Health & Fitness |
| Best use cases | Enterprise financial-services AI programs requiring both scale and deep ML expertise, Cloud-native ML platform builds on GCP, AWS, or Azure at production scale | Retail or hospitality companies wanting computer-vision or recommendation features built into an existing product, Health and fitness apps needing an ML-driven personalization or tracking feature |
| Typical project type | Fixed project | Fixed project |
Quantiphi vs MobiDev: pros and cons
| Quantiphi | |
|---|---|
| + | Founded as an AI-first company rather than a generalist IT firm that later added an AI practice |
| + | Enterprise-scale headcount (2,600+) supports large, multi-region programs |
| + | Strong cloud-native ML platform engineering, reducing gaps between model development and production deployment |
| + | 13 years of continuous focus on applied AI and analytics |
| - | Scale and enterprise sales process may be slower and less accessible for small pilot projects than boutique competitors |
| - | Recent employee counts show a reported year-over-year headcount decline (~4% per one source), worth asking about directly |
| - | Minimum engagement size and standard pricing are not publicly disclosed |
| MobiDev | |
|---|---|
| + | 65+ delivered AI/ML products gives a concrete, countable delivery track record rather than general marketing claims |
| + | Deliberate AI/ML practice build-out since 2018, rather than a very recent pivot |
| + | Named vertical concentration (retail, hospitality, fitness, health) supports domain-specific product experience |
| + | Mid-size team (290–400) balances specialist focus with real delivery capacity |
| - | Narrower industry focus than horizontal AI consultancies serving finance, healthcare, and manufacturing broadly |
| - | Smaller scale than the large enterprise IT firms on this list, limiting very large multi-team programs |
| - | AI/ML sits alongside a broader general custom-software-development practice |
Who should choose Quantiphi?
Quantiphi is the right choice for enterprises, especially in financial services, needing AI delivery at scale with strong cloud-native ML platform engineering..
AI-native firm that reached enterprise scale (2,600+ employees) without pivoting from generalist IT outsourcing.. Minimum engagement starts at Not published. Works best with clients in Financial Services, Healthcare, Media, Technology/SaaS.
Who should choose MobiDev?
MobiDev is the right choice for retail, hospitality, and health/fitness companies wanting a mid-size firm with a proven, product-specific AI/ML delivery track record..
65+ delivered AI/ML products concentrated in retail, hospitality, fitness, and health/wellness verticals.. Minimum engagement starts at $20K. Works best with clients in Retail, Hospitality, Health & Fitness, Sports.
Decision matrix: Quantiphi vs MobiDev
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | Quantiphi |
| You need a large dedicated team for an ongoing programme | MobiDev |
| Your budget is at the lower end | Compare: Quantiphi (Not published) vs MobiDev ($20K) |
| You need specialist depth in a specific vertical | Quantiphi |
| You need staff augmentation or team extension | Neither; consider alternatives that offer staff aug |
| You need consulting before committing to a build | Quantiphi |
Use case fit: Quantiphi vs MobiDev
| Use case | Quantiphi fit | MobiDev fit | Winner |
|---|---|---|---|
| Enterprise financial-services AI programs requiring both scale and deep ML expertise | Strong | Limited | Quantiphi |
| Cloud-native ML platform builds on GCP, AWS, or Azure at production scale | Strong | Limited | Quantiphi |
| Retail or hospitality companies wanting computer-vision or recommendation features built into an existing product | Limited | Strong | MobiDev |
| Health and fitness apps needing an ML-driven personalization or tracking feature | Limited | Strong | MobiDev |
| Fixed-price build | Limited | Limited | Both equally |
| Staff augmentation | Limited | Limited | Both equally |
Verdict: Quantiphi vs MobiDev
Quantiphi (4.4/5) is the stronger overall choice for most Machine Learning Development projects. AI-native firm that reached enterprise scale (2,600+ employees) without pivoting from generalist IT outsourcing.. It is best for enterprises, especially in financial services, needing AI delivery at scale with strong cloud-native ML platform engineering..
MobiDev (4.2/5) is the better choice when retail, hospitality, and health/fitness companies wanting a mid-size firm with a proven, product-specific AI/ML delivery track record.. If your situation matches those criteria, MobiDev is a competitive option.
Related comparisons
Quantiphi vs MobiDev FAQ
Is Quantiphi better than MobiDev?
Quantiphi (4.4/5) scores higher overall, but "better" depends on your use case. Quantiphi is better for enterprises, especially in financial services, needing AI delivery at scale with strong cloud-native ML platform engineering.. MobiDev is better for retail, hospitality, and health/fitness companies wanting a mid-size firm with a proven, product-specific AI/ML delivery track record..
How do Quantiphi and MobiDev differ in pricing?
Quantiphi uses fixed project and managed ai services pricing with a minimum engagement of Not published. MobiDev uses fixed project and dedicated team pricing with a minimum engagement of $20K. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: Quantiphi or MobiDev?
Quantiphi is the larger team and typically the better enterprise-scale choice. For very large programmes, verify team size and compliance coverage directly with each agency before shortlisting.
What are the main differences between Quantiphi and MobiDev?
Quantiphi's primary differentiator is: ai-native firm that reached enterprise scale (2,600+ employees) without pivoting from generalist it outsourcing.. MobiDev's primary differentiator is: 65+ delivered ai/ml products concentrated in retail, hospitality, fitness, and health/wellness verticals.. They also differ in team size (1,001–5,000 vs 201–500), minimum engagement (Not published vs $20K), and primary industries served (Financial Services, Healthcare vs Retail, Hospitality).
Last reviewed: July 2026. Verify all details directly with each agency before making a decision.